Retrieval-Augmented Generation

RAG - Knowledge Base for your AI

Fully leverage the potential of your corporate data while maintaining maximum privacy.

What is Retrieval-Augmented Generation?

RAG is a technique that combines the capabilities of Large Language Models (LLM) with your own, up-to-date, and specific data. Instead of relying only on what it learned during training, the model can 'look up' relevant information in your internal knowledge base.

"Instead of the AI just guessing, it looks in your library and answers based on facts."

Model is using internal data...

Main benefits of RAG

Up-to-dateness and accuracy

The model has access to the latest versions of your documents, guidelines, or manuals in real-time.

100% data privacy

Your sensitive corporate data never leaves your infrastructure. Both indexing and querying take place locally.

Reduction of hallucinations

Because the model draws from specific documents, the risk of AI making up false information is significantly reduced.

Easy knowledge management

Simply upload new documents (PDF, DOCX, TXT) and the AI will immediately start working with them as an expert source.